达观杯文本智能处理挑战赛

版权声明：Geek Song创造，版权所有 https://blog.csdn.net/Geeksongs/article/details/83183360

笔者尝试了一下达观杯的比赛，代码如下图所示：

import pandas as pd

import imp

from sklearn.linear_model import LogisticRegression

from sklearn.feature_extraction.text import CountVectorizer

 

df_test = pd.read_csv(r'testset.csv')

df_train = pd.read_csv(r'trainset.csv')

df_train.drop(columns=['article','id'],inplace=True)

df_test.drop(columns=['article'],inplace=True)

vectorizer = CountVectorizer(ngram_range=(1, 2),min_df=3,max_df=0.9,max_features=10000)

vectorizer.fit(df_train['word_seg'])

x_train =vectorizer.transform(df_train['word_seg'])

x_test =vectorizer.transform(df_test['word_seg'])

y_train =df_train['class']-1

lg = LogisticRegression(C=4,dual=True)

lg.fit(x_train,y_train)

y_test = lg.predict(x_test)

df_test['class'] = y_test.tolist()

df_test['class'] = df_test['class'] + 1

df_result =df_test.loc[:,['id','class']]

df_result.to_csv('./result.csv',index=False)

print("完成")

运行结果是：

pandas.errors.ParserError: Error tokenizing data. C error: out of memory

这是因为我的电脑内存太小，导致了内存溢出，因此换一台电脑就可以得到最终得分为72分的答案了。笔者最终排名位于全国前300名，算是一个个人感觉还不错的成绩了。
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